4 citations · 6 across the 5 of their papers we have counts for
11 papers
Robust multi-rate predictive control using multi-step prediction models learned from data
Enrico Terzi, Lorenzo Fagiano, Marcello Farina +1
This note extends a recently proposed algorithm for model identification and robust MPC of asymptotically stable, linear time-invariant systems subject to process and measurement d…
Stability of discrete-time feed-forward neural networks in NARX configuration
Fabio Bonassi, Marcello Farina, Riccardo Scattolini
The idea of using Feed-Forward Neural Networks (FFNNs) as regression functions for Nonlinear AutoRegressive eXogenous (NARX) models, leading to models herein named Neural NARXs (NN…
Hierarchical routing control in discrete manufacturing plants via model predictive path allocation and greedy path following
Lorenzo Fagiano, Marko Tanaskovic, Lenin Cucas Mallitasig +2
The problem of real-time control and optimization of components' routing in discrete manufacturing plants, where distinct items must undergo a sequence of jobs, is considered. This…
On the stability properties of Gated Recurrent Units neural networks
Fabio Bonassi, Marcello Farina, Riccardo Scattolini
The goal of this paper is to provide sufficient conditions for guaranteeing the Input-to-State Stability (ISS) and the Incremental Input-to-State Stability (δISS) of Gated Recurren…
Supervised MPC control of large-scale electricity networks via clustering methods
Alessio La Bella, Pascal Klaus, Giancarlo Ferrari-Trecate +1
This paper describes a control approach for large-scale electricity networks, with the goal of efficiently coordinating distributed generators to balance unexpected load variations…
Scenario optimization for optimal training of Echo State Networks
Luca Bugliari Armenio, Lorenzo Fagiano, Enrico Terzi +2
Echo State Networks (ESNs) are widely-used Recurrent Neural Networks. They are dynamical systems including, in state-space form, a nonlinear state equation and a linear output tran…